{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 美国新出生人口名字统计"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from matplotlib import pyplot as plt\n",
    "import numpy as np\n",
    "path = '/Users/linqiliang/Documents/PySci/data/pydata-book/ch02/names/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>births</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mary</td>\n",
       "      <td>F</td>\n",
       "      <td>7065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Anna</td>\n",
       "      <td>F</td>\n",
       "      <td>2604</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Emma</td>\n",
       "      <td>F</td>\n",
       "      <td>2003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Elizabeth</td>\n",
       "      <td>F</td>\n",
       "      <td>1939</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        name sex  births\n",
       "0       Mary   F    7065\n",
       "1       Anna   F    2604\n",
       "2       Emma   F    2003\n",
       "3  Elizabeth   F    1939"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names1880 = pd.read_csv(path+'yob1880.txt',names=['name','sex','births'])\n",
    "names1880[:4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "sex\n",
       "F     90993\n",
       "M    110493\n",
       "Name: births, dtype: int64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names1880.groupby('sex')['births'].sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## different years are in different files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "years = range(1880,2011)\n",
    "columns = ['name','sex','births']\n",
    "pieces = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for year in years:\n",
    "    tbirth = pd.read_csv((path+'yob%d.txt') % year,names=['name','sex','births'])\n",
    "    tbirth['year']=year\n",
    "    pieces.append(tbirth)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "names = pd.concat(pieces,ignore_index = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "total_birth = names.pivot_table(values=['births'],index =['year'],columns = ['sex'], aggfunc=np.sum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x17bdfb7d0>"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_birth.plot(title='Total births by sex and year')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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nqC9ZsiQ1atSge/fucUuJPTw86N+/f4rGc3Jyoly5cixcuBBPT0/c3NwoX748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\nwsr/A/YVhGKOWsQNAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x17bdfb150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def add_prop(group):\n",
    "    births = group.births.astype(float)\n",
    "    group['prop'] = births/group.births.sum()\n",
    "    return group\n",
    "names = names.groupby(['year','sex']).apply(add_prop)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>births</th>\n",
       "      <th>year</th>\n",
       "      <th>prop</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mary</td>\n",
       "      <td>F</td>\n",
       "      <td>7065</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.077643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Anna</td>\n",
       "      <td>F</td>\n",
       "      <td>2604</td>\n",
       "      <td>1880</td>\n",
       "      <td>0.028618</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   name sex  births  year      prop\n",
       "0  Mary   F    7065  1880  0.077643\n",
       "1  Anna   F    2604  1880  0.028618"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "names[:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.allclose(names.groupby(['year','sex']).prop.sum(),1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def get_top1000(group):\n",
    "    return   group.sort_values(by='prop',ascending = False)[:1000]\n",
    "top1000 = names.groupby(['year','sex']).apply(get_top1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python2.7/site-packages/ipykernel/__main__.py:1: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
      "  if __name__ == '__main__':\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>sex</th>\n",
       "      <th>births</th>\n",
       "      <th>year</th>\n",
       "      <th>prop</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th>sex</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <th>M</th>\n",
       "      <th>1676644</th>\n",
       "      <td>Jacob</td>\n",
       "      <td>M</td>\n",
       "      <td>21875</td>\n",
       "      <td>2010</td>\n",
       "      <td>0.011523</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   name sex  births  year      prop\n",
       "year sex                                           \n",
       "2010 M   1676644  Jacob   M   21875  2010  0.011523"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top1000[top1000['year']==2010][top1000['sex']=='M'][top1000['name']=='Jacob']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "boys = top1000[top1000.sex == 'M']\n",
    "girls = top1000[top1000.sex == 'F']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "total_births = top1000.pivot_table(values='births',index='year',columns='name',aggfunc = np.sum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x18162b510>"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "subset = total_births[['John','Harry','Mary','Marilyn']]\n",
    "subset.plot(subplots = False,figsize=(20,10),grid=False,title='Number of birth per year')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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qMyaUccymriNJkiRJ5ZKfH3tv1KuX6Uo2rnVrePTRWO+QIUV7f7z7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EBk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\nZoE0r9fc6vN+LIaF0OTQk5Unmw9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9nRc++AIVkYpiN0nOciOZDJ/ct4+729t5bVUV95xz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\nC9WpCAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x18153bcd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# evaluate the name diviserity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "table = top1000.pivot_table(values='prop',index = 'year',columns = 'sex',aggfunc = np.sum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x18168e790>"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "table.plot(title = 'sum of table1000.prop by year and sex',yticks = np.linspace(0,1.2,13),xticks = range(1880,2020,10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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U73j8FO0y/FihXwafm/CpzDOBBRHKPw4sD0sbALwYfG024deoOD18nxH2Fct3VbOfK/x3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\nkpoSCREREUlNiYSIiIik9v8D5soa/03shwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x18154d150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x181815d90>"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "table.plot(title = 'sum of table1000.prop by year and sex')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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4goOhQwe7tGtnaxMg5YlCLv9cNyUIcUSEsrnL3rCuXO5yPFz2YcD+yPt43Tj0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\nCSIiIhLT/wcDi6xIbGWCfQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x17c69fe90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# get the top1000 name's prop in the year born  by sex "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# the last alpha data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "get_last_data= lambda x: x[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "last_letters = names.name.map(get_last_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "last_letters.name = 'last_letter'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    y\n",
       "1    a\n",
       "2    a\n",
       "3    h\n",
       "4    e\n",
       "5    t\n",
       "6    a\n",
       "7    e\n",
       "8    a\n",
       "9    h\n",
       "Name: last_letter, dtype: object"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "last_letters[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "table = names.pivot_table(values = 'births',index = last_letters, columns = ['sex','year'],aggfunc = np.sum )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th>sex</th>\n",
       "      <th colspan=\"10\" halign=\"left\">F</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"10\" halign=\"left\">M</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th>1880</th>\n",
       "      <th>1881</th>\n",
       "      <th>1882</th>\n",
       "      <th>1883</th>\n",
       "      <th>1884</th>\n",
       "      <th>1885</th>\n",
       "      <th>1886</th>\n",
       "      <th>1887</th>\n",
       "      <th>1888</th>\n",
       "      <th>1889</th>\n",
       "      <th>...</th>\n",
       "      <th>2001</th>\n",
       "      <th>2002</th>\n",
       "      <th>2003</th>\n",
       "      <th>2004</th>\n",
       "      <th>2005</th>\n",
       "      <th>2006</th>\n",
       "      <th>2007</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2010</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>last_letter</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>31446.0</td>\n",
       "      <td>31581.0</td>\n",
       "      <td>36536.0</td>\n",
       "      <td>38330.0</td>\n",
       "      <td>43680.0</td>\n",
       "      <td>45408.0</td>\n",
       "      <td>49100.0</td>\n",
       "      <td>48942.0</td>\n",
       "      <td>59442.0</td>\n",
       "      <td>58631.0</td>\n",
       "      <td>...</td>\n",
       "      <td>39124.0</td>\n",
       "      <td>38815.0</td>\n",
       "      <td>37825.0</td>\n",
       "      <td>38650.0</td>\n",
       "      <td>36838.0</td>\n",
       "      <td>36156.0</td>\n",
       "      <td>34654.0</td>\n",
       "      <td>32901.0</td>\n",
       "      <td>31430.0</td>\n",
       "      <td>28438.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>50950.0</td>\n",
       "      <td>49284.0</td>\n",
       "      <td>48065.0</td>\n",
       "      <td>45914.0</td>\n",
       "      <td>43144.0</td>\n",
       "      <td>42600.0</td>\n",
       "      <td>42123.0</td>\n",
       "      <td>39945.0</td>\n",
       "      <td>38862.0</td>\n",
       "      <td>38859.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>27113.0</td>\n",
       "      <td>27238.0</td>\n",
       "      <td>27697.0</td>\n",
       "      <td>26778.0</td>\n",
       "      <td>26078.0</td>\n",
       "      <td>26635.0</td>\n",
       "      <td>26864.0</td>\n",
       "      <td>25318.0</td>\n",
       "      <td>24048.0</td>\n",
       "      <td>23125.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>609.0</td>\n",
       "      <td>607.0</td>\n",
       "      <td>734.0</td>\n",
       "      <td>810.0</td>\n",
       "      <td>916.0</td>\n",
       "      <td>862.0</td>\n",
       "      <td>1007.0</td>\n",
       "      <td>1027.0</td>\n",
       "      <td>1298.0</td>\n",
       "      <td>1374.0</td>\n",
       "      <td>...</td>\n",
       "      <td>60838.0</td>\n",
       "      <td>55829.0</td>\n",
       "      <td>53391.0</td>\n",
       "      <td>51754.0</td>\n",
       "      <td>50670.0</td>\n",
       "      <td>51410.0</td>\n",
       "      <td>50595.0</td>\n",
       "      <td>47910.0</td>\n",
       "      <td>46172.0</td>\n",
       "      <td>44398.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>33378.0</td>\n",
       "      <td>34080.0</td>\n",
       "      <td>40399.0</td>\n",
       "      <td>41914.0</td>\n",
       "      <td>48089.0</td>\n",
       "      <td>49616.0</td>\n",
       "      <td>53884.0</td>\n",
       "      <td>54353.0</td>\n",
       "      <td>66750.0</td>\n",
       "      <td>66663.0</td>\n",
       "      <td>...</td>\n",
       "      <td>145395.0</td>\n",
       "      <td>144651.0</td>\n",
       "      <td>144769.0</td>\n",
       "      <td>142098.0</td>\n",
       "      <td>141123.0</td>\n",
       "      <td>142999.0</td>\n",
       "      <td>143698.0</td>\n",
       "      <td>140966.0</td>\n",
       "      <td>135496.0</td>\n",
       "      <td>129012.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>f</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1758.0</td>\n",
       "      <td>1817.0</td>\n",
       "      <td>1819.0</td>\n",
       "      <td>1904.0</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>1968.0</td>\n",
       "      <td>2090.0</td>\n",
       "      <td>2195.0</td>\n",
       "      <td>2212.0</td>\n",
       "      <td>2255.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>g</th>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2151.0</td>\n",
       "      <td>2084.0</td>\n",
       "      <td>2009.0</td>\n",
       "      <td>1837.0</td>\n",
       "      <td>1882.0</td>\n",
       "      <td>1929.0</td>\n",
       "      <td>2040.0</td>\n",
       "      <td>2059.0</td>\n",
       "      <td>2396.0</td>\n",
       "      <td>2666.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>h</th>\n",
       "      <td>4863.0</td>\n",
       "      <td>4784.0</td>\n",
       "      <td>5567.0</td>\n",
       "      <td>5701.0</td>\n",
       "      <td>6602.0</td>\n",
       "      <td>6624.0</td>\n",
       "      <td>7146.0</td>\n",
       "      <td>7141.0</td>\n",
       "      <td>8630.0</td>\n",
       "      <td>8826.0</td>\n",
       "      <td>...</td>\n",
       "      <td>85959.0</td>\n",
       "      <td>88085.0</td>\n",
       "      <td>88226.0</td>\n",
       "      <td>89620.0</td>\n",
       "      <td>92497.0</td>\n",
       "      <td>98477.0</td>\n",
       "      <td>99414.0</td>\n",
       "      <td>100250.0</td>\n",
       "      <td>99979.0</td>\n",
       "      <td>98090.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>i</th>\n",
       "      <td>61.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>105.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>134.0</td>\n",
       "      <td>...</td>\n",
       "      <td>20980.0</td>\n",
       "      <td>23610.0</td>\n",
       "      <td>26011.0</td>\n",
       "      <td>28500.0</td>\n",
       "      <td>31317.0</td>\n",
       "      <td>33558.0</td>\n",
       "      <td>35231.0</td>\n",
       "      <td>38151.0</td>\n",
       "      <td>40912.0</td>\n",
       "      <td>42956.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>j</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>1069.0</td>\n",
       "      <td>1088.0</td>\n",
       "      <td>1203.0</td>\n",
       "      <td>1094.0</td>\n",
       "      <td>1291.0</td>\n",
       "      <td>1241.0</td>\n",
       "      <td>1254.0</td>\n",
       "      <td>1381.0</td>\n",
       "      <td>1416.0</td>\n",
       "      <td>1459.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 262 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "sex                F                                                        \\\n",
       "year            1880     1881     1882     1883     1884     1885     1886   \n",
       "last_letter                                                                  \n",
       "a            31446.0  31581.0  36536.0  38330.0  43680.0  45408.0  49100.0   \n",
       "b                NaN      NaN      NaN      NaN      NaN      NaN      NaN   \n",
       "c                NaN      NaN      5.0      5.0      NaN      NaN      NaN   \n",
       "d              609.0    607.0    734.0    810.0    916.0    862.0   1007.0   \n",
       "e            33378.0  34080.0  40399.0  41914.0  48089.0  49616.0  53884.0   \n",
       "f                NaN      NaN      NaN      NaN      NaN      NaN      NaN   \n",
       "g                7.0      5.0     12.0      8.0     24.0     11.0     18.0   \n",
       "h             4863.0   4784.0   5567.0   5701.0   6602.0   6624.0   7146.0   \n",
       "i               61.0     78.0     81.0     76.0     84.0     92.0     85.0   \n",
       "j                NaN      NaN      NaN      NaN      NaN      NaN      NaN   \n",
       "\n",
       "sex                                       ...            M            \\\n",
       "year            1887     1888     1889    ...         2001      2002   \n",
       "last_letter                               ...                          \n",
       "a            48942.0  59442.0  58631.0    ...      39124.0   38815.0   \n",
       "b                NaN      NaN      NaN    ...      50950.0   49284.0   \n",
       "c                NaN      NaN      NaN    ...      27113.0   27238.0   \n",
       "d             1027.0   1298.0   1374.0    ...      60838.0   55829.0   \n",
       "e            54353.0  66750.0  66663.0    ...     145395.0  144651.0   \n",
       "f                NaN      NaN      NaN    ...       1758.0    1817.0   \n",
       "g               25.0     44.0     28.0    ...       2151.0    2084.0   \n",
       "h             7141.0   8630.0   8826.0    ...      85959.0   88085.0   \n",
       "i              105.0    141.0    134.0    ...      20980.0   23610.0   \n",
       "j                NaN      NaN      NaN    ...       1069.0    1088.0   \n",
       "\n",
       "sex                                                                      \\\n",
       "year             2003      2004      2005      2006      2007      2008   \n",
       "last_letter                                                               \n",
       "a             37825.0   38650.0   36838.0   36156.0   34654.0   32901.0   \n",
       "b             48065.0   45914.0   43144.0   42600.0   42123.0   39945.0   \n",
       "c             27697.0   26778.0   26078.0   26635.0   26864.0   25318.0   \n",
       "d             53391.0   51754.0   50670.0   51410.0   50595.0   47910.0   \n",
       "e            144769.0  142098.0  141123.0  142999.0  143698.0  140966.0   \n",
       "f              1819.0    1904.0    1985.0    1968.0    2090.0    2195.0   \n",
       "g              2009.0    1837.0    1882.0    1929.0    2040.0    2059.0   \n",
       "h             88226.0   89620.0   92497.0   98477.0   99414.0  100250.0   \n",
       "i             26011.0   28500.0   31317.0   33558.0   35231.0   38151.0   \n",
       "j              1203.0    1094.0    1291.0    1241.0    1254.0    1381.0   \n",
       "\n",
       "sex                              \n",
       "year             2009      2010  \n",
       "last_letter                      \n",
       "a             31430.0   28438.0  \n",
       "b             38862.0   38859.0  \n",
       "c             24048.0   23125.0  \n",
       "d             46172.0   44398.0  \n",
       "e            135496.0  129012.0  \n",
       "f              2212.0    2255.0  \n",
       "g              2396.0    2666.0  \n",
       "h             99979.0   98090.0  \n",
       "i             40912.0   42956.0  \n",
       "j              1416.0    1459.0  \n",
       "\n",
       "[10 rows x 262 columns]"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "table[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "subtable = table.reindex(columns = [1910,1960,2010],level = 'year')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th>sex</th>\n",
       "      <th colspan=\"3\" halign=\"left\">F</th>\n",
       "      <th colspan=\"3\" halign=\"left\">M</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th>1910</th>\n",
       "      <th>1960</th>\n",
       "      <th>2010</th>\n",
       "      <th>1910</th>\n",
       "      <th>1960</th>\n",
       "      <th>2010</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>last_letter</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>108376.0</td>\n",
       "      <td>691247.0</td>\n",
       "      <td>670605.0</td>\n",
       "      <td>977.0</td>\n",
       "      <td>5204.0</td>\n",
       "      <td>28438.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>NaN</td>\n",
       "      <td>694.0</td>\n",
       "      <td>450.0</td>\n",
       "      <td>411.0</td>\n",
       "      <td>3912.0</td>\n",
       "      <td>38859.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>5.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>946.0</td>\n",
       "      <td>482.0</td>\n",
       "      <td>15476.0</td>\n",
       "      <td>23125.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>6750.0</td>\n",
       "      <td>3729.0</td>\n",
       "      <td>2607.0</td>\n",
       "      <td>22111.0</td>\n",
       "      <td>262112.0</td>\n",
       "      <td>44398.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>e</th>\n",
       "      <td>133569.0</td>\n",
       "      <td>435013.0</td>\n",
       "      <td>313833.0</td>\n",
       "      <td>28655.0</td>\n",
       "      <td>178823.0</td>\n",
       "      <td>129012.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "sex                 F                            M                    \n",
       "year             1910      1960      2010     1910      1960      2010\n",
       "last_letter                                                           \n",
       "a            108376.0  691247.0  670605.0    977.0    5204.0   28438.0\n",
       "b                 NaN     694.0     450.0    411.0    3912.0   38859.0\n",
       "c                 5.0      49.0     946.0    482.0   15476.0   23125.0\n",
       "d              6750.0    3729.0    2607.0  22111.0  262112.0   44398.0\n",
       "e            133569.0  435013.0  313833.0  28655.0  178823.0  129012.0"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "subtable.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "subtable.sum()\n",
    "letter_prop = subtable/subtable.sum().astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x183ed8650>"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2,1,figsize=(10,8))\n",
    "letter_prop['M'].plot(kind='bar',rot = 0,ax = axes[0],title = 'Male')\n",
    "letter_prop['F'].plot(kind='bar',rot = 0,ax = axes[1],title = 'Female',legend =False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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fzVm/fj2LFi1ijz32AGD8+PEcddRRzJw5k1NOOaXp+Jdffpnq6mr++Mc/suuu\nu3bY9w033MCLL77IU089xdixYwH49Kc/zf7778+1117LpZdeWtS5bAnDjyRJktQFo4Cx5R5EiT7x\niU+0Kdtnn33Yf//9WbJkSVPZ3LlzOfbYY5uCD8DEiRPZb7/9mDNnTovw09UA9rOf/Yzx48c3BR+A\nmpoaJk6cyJw5c3o1/LjhgSRJklShVq9e3XQtz2uvvcbrr7/OwQcf3KbeIYccwjPPPFN0+yklnnvu\nuQ7bfPHFF3n33XeLH3iJDD+SJElSBZo9ezYrVqzgS1/6EgArV64EYPjw4W3qDh8+nDfffJONGzcW\n1cebb77Jhg0bOmwT8qGrtxh+JEmSpAqzdOlSvv3tb/NXf/VXnHTSSQCsX78egEGDBrWpX1VV1aJO\nV/VEm1vC8CNJkiRVkNdff51jjjmGnXbaif/zf/4PEQHA4MGDAdiwYUObY3KFne4a63RVT7S5Jdzw\nQJIkSaoQ77zzDkcffTTvvPMOv/rVr9h9992bXmtchta4/K25lStXsvPOOzNgwICi+tt5550ZNGhQ\nh20277c3lDTzExHfiojlEbE+Ip6IiPGd1D0lIh6LiDcLjwda14+IWyJiU6vHvaWMTZIkSVJbGzZs\n4LjjjuP3v/8999xzDzU1NS1eHzFiBLvuuitPP/10m2Pnz5/P6NGji+4zIjjggAPabfPJJ5/kox/9\nKEOHDi263VIVHX4iYjJwLXARMAZ4Frg/IjIdHPIp4HZgAvAJ4BXg/0VE64h3H7AbsHvhUVvs2CRJ\nkiS1tWnTJiZNmsQTTzzBHXfcwSGHHNJuvc9//vP84he/YMWKFU1lDz30EC+88AKTJk0qqe8vfOEL\nPPXUUyxcuLCpbNmyZTz88MMlt1mqUpa9TQNuSinNAoiIbwLHACcDV7WunFL6SvPnEXEK8HlgIjC7\n2UsbUkpvlDAeSZIkqcct2XyVrbb/M888k7vvvpu/+7u/I5vNctttt7V4/cQTTwTgvPPO44477mDC\nhAmcfvrprF27lmuuuYaDDjqIr371qy2OmT17Nn/4wx+atqqeN28el112GQAnnXQSH/nIRwA49dRT\nufnmm/nsZz/LWWedxXbbbUddXR3Dhw/nzDPP3IKzKl5R4SciBgDjgMsby1JKKSIeBA7rYjPbAwOA\nN1uVT4iI1cBbwMPA+Sml1nUkSZKkXpXJZBhSVcWUwgX65TSkqqrpvjzFePbZZ4kI7r77bu6+++42\nrzeGn5EbBs49AAAgAElEQVQjRzJv3jzOPPNMzj33XAYOHMixxx7LNddc0+Z6nx/96Ec89thjQH55\n26OPPsqjjz4KwOGHH94UfoYOHcq8efOYNm0al112GZs2beKII45gxowZ7LLLLkWfy5YoduYnA2wL\nrG5VvhqoaVu9XVcCK4AHm5XdB/wMWA7sDfw7cG9EHJZSSkWOUZIkSeo21dXVLFm2jGw2W+6hkMlk\nqK6uLvq4Rx55pMt1R40axX333detbY4YMYKf/vSnXa7fU7prt7cANhtSIuLfgEnAp1JK7zWWp5Tm\nNKv2fET8D/Ai+euEOvypTps2jR133LFFWW1tLbW1Xi4kSZKk7lNdXV1S6FD3qq+vp76+vkXZmjVr\nunx8seEnC3xAfmOC5obRdjaohYg4CzgbmJhSer6zuiml5RGRBfahk/BTV1fH2LFjuzJuSZIkSX1c\nexMdCxcuZNy4cV06vqjd3lJKG4EF5DcrACDyd0WaCPy6o+Mi4l+B7wBHp5Se2Vw/ETES2AVouyG4\nJEmSJJWglPv8zAC+HhEnRcTHgB8CQ4CZABExKyKaNkSIiLOB6eR3g2uIiN0Kj+0Lr28fEVdFxKER\nsWdETAT+L/ACcP+WnJwkSZIkNSr6mp+U0pzCPX0uIb/8bRH5GZ3GbapHAu83O+SfyO/udkerpr5b\naOMD4EDgJODDwGvkQ8+FhZkmSZIkSdpiJW14kFK6Ebixg9eObPV8r820lQM+Xco4JEmSJKmrSln2\nJkmSJEl9juFHkiRJUkXorvv8SJIkSf3CkiVLyj0ENdOdfx6GH0mSJAnIZDIMGTKEKVOmlHsoamXI\nkCFkMpktbsfwI0mSJAHV1dUsWbKEbDZb7qGolUwmQ3V19Ra3Y/iRJEmSCqqrq7vlQ7a2Tm54IEmS\nJKkiGH4kSZIkVQTDjyRJkqSKYPiRJEmSVBEMP5IkSZIqguFHkiRJUkUw/EiSJEmqCIYfSZIkSRXB\n8CNJkiSpIhh+JEmSJFUEw48kSZKkimD4kSRJklQRDD+SJEmSKoLhR5IkSVJFMPxIkiRJqgiGH0mS\nJEkVwfAjSZIkqSIYfiRJkiRVhJLCT0R8KyKWR8T6iHgiIsZ3UveUiHgsIt4sPB5or35EXBIRr0XE\nukKdfUoZmyRJkiS1p+jwExGTgWuBi4AxwLPA/RGR6eCQTwG3AxOATwCvAP8vIoY3a/Mc4NvAN4BD\ngHcLbQ4sdnySJEmS1J5SZn6mATellGallJYC3wTWASe3Vzml9JWU0g9TSs+llF4ATin0O7FZtdOB\n6Smlu1NKvwVOAkYAnythfJIkSZLURlHhJyIGAOOAhxrLUkoJeBA4rIvNbA8MAN4stLkXsHurNt8B\nniyiTUmSJEnqVLEzPxlgW2B1q/LV5ANMV1wJrCAfmCgcl7awTUmSJEnq1Hbd1E6QDzCdV4r4N2AS\n8KmU0ntb2ua0adPYcccdW5TV1tZSW1u7uaFIkiRJ6mPq6+upr69vUbZmzZouH19s+MkCHwC7tSof\nRtuZmxYi4izgbGBiSun5Zi+tIh90dmvVxjDgmc7arKurY+zYsV0buSRJkqQ+rb2JjoULFzJu3Lgu\nHV/UsreU0kZgAc02K4iIKDz/dUfHRcS/At8Bjk4ptQg0KaXl5ANQ8zY/BBzaWZuSJEmSVIxSlr3N\nAG6NiAXAfPK7vw0BZgJExCzg1ZTSeYXnZwOXALVAQ0Q0zhr9KaX0buH/vwecHxG/B14GpgOvAj8v\nYXySJEmS1EbR4SelNKdwT59LyC9VW0R+RueNQpWRwPvNDvkn8ru73dGqqe8W2iCldFVEDAFuAj4M\n/BL4TBeuC5IkSZKkLilpw4OU0o3AjR28dmSr53t1sc2LgYtLGY8kSZIkbU4pNzmVJEmSpD7H8CNJ\nkiSpIhh+JEmSJFUEw48kSZKkimD4kSRJklQRDD+SJEmSKoLhR5IkSVJFMPxIkiRJqgiGH0mSJEkV\nwfAjSZIkqSIYfiRJkiRVBMOPJEmSpIpg+JEkSZJUEQw/kiRJkiqC4UeSJElSRTD8SJIkSaoIhh9J\nkiRJFcHwI0mSJKkiGH4kSZIkVQTDjyRJkqSKYPiRJEmSVBG2K/cAJEmSJJVfQ0MD2Wy2RVkmk6G6\nurpMI+p+hh9JkiSpwjU0NFDzsRpy63MtyqsGV7Fs6bJ+E4AMP5IkSVKFy2az+eBzApBpLITc3BzZ\nbLbfhJ+SrvmJiG9FxPKIWB8RT0TE+E7qfjwi7ijU3xQRp7VT56LCa80fi0sZmyRJkqQSZYARhUdm\nM3X7oKLDT0RMBq4FLgLGAM8C90dERz+eIcCLwDnAyk6a/i2wG7B74fHXxY5NkiRJkjpSyszPNOCm\nlNKslNJS4JvAOuDk9iqnlJ5OKZ2TUpoDvNdJu++nlN5IKb1eeLxZwtgkSZIkqV1FXfMTEQOAccDl\njWUppRQRDwKHbeFY9o2IFUAO+A1wbkrplS1sU5KkFlrvZrRkyZIyjkaS1JuK3fAgA2wLrG5Vvhqo\n2YJxPAF8FVgGDAcuBh6LiP1TSu9uQbuSJDXpaDcjSVJl6K7d3gJIpR6cUrq/2dPfRsR84A/AJOCW\njo6bNm0aO+64Y4uy2tpaamtrSx2KJKkfa3c3o98Bj5RxUJKkLquvr6e+vr5F2Zo1a7p8fLHhJwt8\nQH5jguaG0XY2qGQppTUR8QKwT2f16urqGDt2bHd1qz6iEm7AJamHNe5mBPnfbJKkPqG9iY6FCxcy\nbty4Lh1fVPhJKW2MiAXAROAugIiIwvPrimmrMxExFNgbmNVdbap/aGhooKZmFLncuhblVVVDWLZs\niQFIkiRJHSplt7cZwNcj4qSI+BjwQ/LbWc8EiIhZEdG0IUJEDIiIgyJiNDAQ2KPwfO9mda6OiE9G\nxJ4R8b+AO4H3gZZzWqp42Wy2EHxmAwsKj9nkcuvazAZJkiRJzRV9zU9KaU7hnj6XkF/+tgg4OqX0\nRqHKSPLBpdEI4Bn+fE3QWYXHPODIZsfcDuwCvAH8CvhESumPxY5PlWIU4JJHSZ1zZzdJUnMlbXiQ\nUroRuLGD145s9fwPbGaGKaXkDgWSpG7V0TJZSVLlKmXZmyRJW732l8lOL++gJEll1V1bXUuStJVq\nvkzWZW+SVMmc+ZEkSZJUEQw/kiRJkiqC4UeSJElSRTD8SJIkSaoIhh9JkiRJFcHd3iRJkrqo9Y1z\nATKZDNXV1WUakaRiGH4kSZK6oKMb51ZVDWHZsiUGIKkPcNmbJElSF7R/49zZ5HLr2swGSdo6OfMj\nSZJUlOY3zpXUlzjzI0mSJKkiGH4kSZIkVQSXvalbuQuOJEmStlaGH3WbhoYGaj5WQ259rkV51eAq\nli1dZgCSJElSWRl+1G2y2Ww++JwAZBoLITc3RzabNfxIkiSprAw/6n4ZYES5ByFJkiS15IYHkiRJ\nkiqC4UeSJElSRXDZm0rWeme3JUuWlHE0kiRJUucMPypJQ0MDNTWjyOXWlXsokiRJUpe47E0lyWaz\nheAzG1hQeEwv76AkSZKkTjjzoy00Chhb+H+XvUmSJGnr5cyPJEmSpIpQUviJiG9FxPKIWB8RT0TE\n+E7qfjwi7ijU3xQRp21pm5IkSZJUrKKXvUXEZOBa4OvAfGAacH9E7JdSyrZzyBDgRWAOUNdNbUqS\nulHr3RsBMpkM1dXVZRqRJEndr5RrfqYBN6WUZgFExDeBY4CTgataV04pPQ08Xah7ZXe0KUnqPg0N\nDdR8rIbc+lyL8qrBVSxbuswAJEnqN4oKPxExABgHXN5YllJKEfEgcFgpA+iJNiVJXZfNZvPB5wQg\n01gIubk5stms4Ufqgtb3unPmVNo6FTvzkwG2BVa3Kl8N1JQ4hp5oU5JUrAwwotyDkPqalRAwZcqU\nFqXOnEpbp+7a6jqA1E1t9WSbkiRJ3ejt/KcVZ06lPqHY8JMFPgB2a1U+jLYzNz3e5rRp09hxxx1b\nlNXW1lJbW1viUCRJkkrgzKnUK+rr66mvr29RtmbNmi4fX1T4SSltjIgFwETgLoCIiMLz64ppqzva\nrKurY+zYsZ1VkSRJktRPtDfRsXDhQsaNG9el40tZ9jYDuLUQWBq3pR4CzASIiFnAqyml8wrPBwAf\nJ7+MbSCwR0QcBPwppfRiV9qUJEmSpC1VdPhJKc2JiAxwCfmlaouAo1NKbxSqjATeb3bICOAZ/nz9\nzlmFxzzgyC62KUmSJElbpKQND1JKNwI3dvDaka2e/wHYZkvalCRJkqQttdlQIkmSJEn9geFHkiRJ\nUkUw/EiSJEmqCN11k1NJkqStTkNDA9lstkVZJpPx5qNShTL8SJKkfqmhoYFRNTWsy+ValA+pqmLJ\nsmUGIKkCGX7UbyxZsqTFc7/Zk6TKls1mWZfLMRsYVShbAkzJ5chms/6OkCqQ4Uf9wEoImDJlSovS\nqsFVLFvqN3uSVOlGAWPLPQhJWwXDj/qBt/O30D0ByBSKspCb6zd7kiRJ+jPDj/qPDDCi3IOQJEnS\n1sqtriVJkiRVBGd+JEmSpArTehv41htH9VeGH0mSJKmCNDQ0UFMzilxuXbmH0utc9iZJkiRVkGw2\nWwg+s4EFhcf08g6qlzjzI0mStJVrvUQJvJ+dukPzjeBd9iZJkqQy62iJUlXVEJYtW2IAkopg+JEk\ndaj1BbB+0yz1vpZLlEYVSpeQy03xfnZSkQw/6tf84CaV6E/5i0KnTJnSonhIVRVLli3z75FUFs2X\nKEkqheFH/ZMf3KQtk4NNtP6eGabkcn7TLEnqsww/6p/84CZ1qJh7O/g9s1S63lh94AoHqTiGH/Vr\nfnCTWqrkezuof9mqdz/rldUHKyHa9lE1uIplS13hIHXE8CNJFaT9C6fvBS4o36CkIm31u5/1yuqD\ntyEBJwCZQlEWcnNd4SB1xvAjSRWp8u7toP6jr+x+1iurDzLAiJ7uROo/DD+SJKmPcnGzpOIYfiRJ\nPW6rvj5DktSp/rSxhuFHktSjtvrrMyRJ7euHtw7ZppSDIuJbEbE8ItZHxBMRMX4z9b8YEUsK9Z+N\niM+0ev2WiNjU6nFvKWOTJG1dWl6fsaDwmE0ut67NbJAkaSvSbPOOP//rDesKm3f0RUXP/ETEZOBa\n4OvAfGAacH9E7JdSavNTiIjDgNuBc4B7gC8D/zcixqSUFjereh/wVSAKzzcUOzZJ0tbM6zMkqS/q\nT/96lzLzMw24KaU0K6W0FPgmsA44uYP6pwP3pZRmpJSWpZQuAhYC325Vb0NK6Y2U0uuFx5oSxiZJ\nkiRJ7Spq5iciBgDjgMsby1JKKSIeBA7r4LDDyM8UNXc/cHyrsgkRsRp4C3gYOD+l9GYx45PUu7yI\nXZIk9SXFLnvLANsCq1uVrwZqOjhm9w7q797s+X3Az4DlwN7AvwP3RsRhKaVU5Bgl9YKGhgZG1dSw\nLpdrUd6XL4LcGhgoJUnqOd2121uQv89wSfVTSnOavfZ8RPwP8CIwAXiko0amTZvGjjvu2KKstraW\n2traIoYiqRTZbJZ1uVwP38G8sjQ0NFDzsRpy61sGyqrBVSxbaqCUJKm+vp76+voWZWvWdP1qmWLD\nTxb4ANitVfkw2s7uNFpVZH1SSssjIgvsQyfhp66ujrFj+8vlV1Lf1J8ugiy3bDabDz4nkJ9nB8hC\nbq6BUpIkaH+iY+HChYwbN65LxxcVflJKGyNiATARuAsgIqLw/LoODvtNO68fVShvV0SMBHYBVhYz\nPkndw6VXZZYBRpR7EJIk9T+lLHubAdxaCEGNW10PAWYCRMQs4NWU0nmF+t8H5kXEmeS3uq4lv2nC\nPxbqbw9cRP6an1XkZ3uuBF4gvzGCpF7kDSklSVJ/VXT4SSnNiYgMcAn55WyLgKNTSm8UqowE3m9W\n/zcRUQtcVnj8Dji+2T1+PgAOBE4CPgy8Rj70XJhS2ljSWUkqWcsbUv75ap5cbopLr6Ru5iyrJPWu\nkjY8SCndCNzYwWtHtlP2M/IzO+3VzwGfLmUcknqSV/NIPckdEyWp95Vyk1NJkrSFmu+YuKDwmA2s\nK+yYKEnqft211bWkCrBkyZJ2/19S6ZxjlaTeY/iR1AUrIWDKlCnlHki/0vp6DwOlJEk9y/AjqQve\nzt+WuPn9Z35HJ3fh0uZ0tKueJEnqOYYfSV3X/P4zXpKwRdrfVe9e4ILyDaoMWs92udOZJKknGX4k\nqayaX/FRScve2l9KWTW4imVL3elMktQzDD+SpDJoZyllFnJzc95PSlvEjVkkdcbwI0kqn+ZLKaUt\n4sYskjbP8CNJkvoBN2aRtHmGH0mS1H+4MYukTmxT7gFIkiRJUm9w5keStFVx+2tJUk8x/KhX+GFG\n3amhoYFstuV6Ft9T/cCf8ssRWl+wPqSqiiXL3P5a6ip/50odM/yoZ/lhRt2soaGBUTU1rMvlWpT7\nnuoHcrCJlrd9XQJMybn9tdQl/s6VNsvwUyatv7nut9/K+GFG3SybzbIul/M91Y81v+2rpCL4O1fa\nLMNPGbT3zXV//1bGDzPqbpX2nnIZi6SuqrR/H6ViGH7KoPU3134rI6lDLmPpk7wuTZK2ToafMvKb\nGUmb5TKWPqehoYGamlHkcutalFdVDWHZsiX+mUl9nF9u9G0VH358A0vqC/yypO/IZrOF4NMysuZy\nUwysUh/npjt9X0WHH9/AkqSe0zayNr92q/V1XJK2fm660/dVdPiptDews1ySVC4rIdpeuyWpb3I2\nvu+q6PDTqBLewM5y9S8GWamveRsScAKQKRT9DnikfCOSpEpk+KkQlTbL1Z81NDRQ87EacutbBtmq\nwVUsW2qQlbZqGWBE4f+znVWUpJb84rN7bFPuAZRDfX19v++3oaGBhQsXsnDhQi6//PKmteWNs1xj\n+XMI6jH/09MdbCV90rt/ttlsNh98TgCOBL4OnAC59bk2/yj2mAr4OZezT6BsP2P77b/9VsLvvhYq\n6M+2XP1Wwnuqo89Tvam+vr5pBc+4ceNaPEbV1NDQ0NAzHffT91RJ4ScivhURyyNifUQ8ERHjN1P/\nixGxpFD/2Yj4TDt1LomI1yJiXUQ8EBH7lDK2rujvf1kbZwYa/2J85zvfKc86c8NPz8oAr5L/Fjmz\nmbrdrYJ+zn5ws9++3m/jh7cf/vCHTR/ieuzDUjv8O9R/++2Pn6eah5177rmH/Wr2K/vnqfr6+hYr\neBYUHrOBdbke/OKzn76nil72FhGTgWvJf988H5gG3B8R+6WU2vz0I+Iw4HbgHOAe4MvA/42IMSml\nxYU65wDfBqYCy4FLC22OSim9V8qJVfLUYIuZgQzw38DeuLa8BzS+z9asWcPChQuBynmfSdr6tV4m\nO27cOMBlslJ7OrpHV09/nirmM2slXKfe00q55mcacFNKaRZARHwTOAY4GbiqnfqnA/ellGYUnl8U\nEX9LPuyc2qzO9JTS3YU2TwJWA58D5hQ7wI7evIMGVfGzn93R9EG1v2wz2vovTdN5Na4trwJ2KsfI\n+jc/VEja2rT3+6Dpy7CngU8DWcjN9XpPqbW29+i6F7igRz9PeVPk3ldU+ImIAcA44PLGspRSiogH\ngcM6OOww8jNFzd0PHF9o86PA7sBDzdp8JyKeLBxbdPhp/wZzv2TDe2dw7LHHAn/+oNrd2kvvGzZs\nYNCgQT0Sujr8lkI9rsUMW6sPFb/85S8ZNerPV1VtyWxQh+G2Ha1fcxZKqhyd/j7IkP/gNuLPRf57\noe5UrhU3PdNv4/xKz39J3tlNkRs/S6xZs6bffGFfjJ56TxU785MBtiU/K9PcaqCmg2N276D+7oX/\n3438BqCd1WmtCjr+EPjn8uXNSpflexkD/AH4S+D1fPG9/PntvbxNG123cuVKTjjhC7z3Xq7DOs1D\nV2O/W9LnkiVLCn9pvgYML5T+D/Dz/DaqWeAdoKFln3RDv21bfDz/n3L2+w7wXPf3C/DGG2+0+Eu4\nfHmhxbeA98ifc/5WHm3WBFcNHMgdc+cyfPhwitHpe6r5+XZjv+X6s4W2P2OAbbbZhk2bNgHw6quv\ncu+99/Zqv6+++iq33XZbm7E0ymQy7LrrrkX3Wa73cjn63Wr/veiH/Xb6+6AH/r1o1Nt/hyrxz7Yc\n/ULX/myz2Sz/9q//Sm7jxhb1evo91d39tv059+afbfPPrM8ALf+OPvbYYz3Ub/94TzUbS9Xm+o+U\nUpcHGxHDgRXAYSmlJ5uVXwX8dUrpf7VzzAbgpJTST5uVnQqcn1IaUbgm6FfAiJTS6mZ15gDvp5S+\n3E6bXwZu6/LAJUmSJPV3J6aUbu+sQrEzP1ngA/KzNc0No+3MTaNVm6m/ivyXULu1amMYjdG3rfuB\nE4GXgY6nWSRJkiT1d1XAX5DPCJ0qKvyklDZGxAJgInAXQERE4fl1HRz2m3ZeP6pQTkppeUSsKtR5\nrtDmh4BDgRs6GMcfye8gJ0mSJEm/7kqlUnZ7mwHcWghBjVtdDwFmAkTELODVlNJ5hfrfB+ZFxJnk\nt7quJb9pwj82a/N7wPkR8XvysznTyd/B5OcljE+SJEmS2ig6/KSU5kREBriE/FK1RcDRKaU3ClVG\nAu83q/+biKgFLis8fgcc33iPn0KdqyJiCHAT8GHgl8BnSr3HjyRJkiS1VtSGB5IkSZLUV21T7gH0\ndxHxSETM2HzN/qsSfgYR8Z8R8ceI+CAiDiz3eHpCuf8cy9V/RNwSEXN7qa+K/BlLktRbSrnmR1Iz\nEfFp4CTgU+S3v892foRK9PfAxs3W6n6nkd+RUpK2OhHxCPBMSunMco9F6gsMP9KW2wdY2fzeV+p+\nKaW3y9Tv2nL0K6l7RMSAlFI5vjiRtBWqqGVvEXF0RPwyIt6KiGxE3B0RH+2FrreLiOsj4u2IeCMi\nLumFPom8syPidxGRi4iXI+LcHu5zSETMioi1EbGisMtfjyuc67kR8VJErIuIZyLi873Q7y3kt3Gv\njohNEfFSL/Q5NCJui4g/FX7GZ/TicqVtIuLKwhK/lRFxUS/0CVTGsrd2+j4mItYUNo3pFwp/jtdF\nRF1EvBkRqyLia4V/O/53RLxT+Dfr0z08hu/39ns5IgYWzn11RKwv/D46uIf7fKTw+6dXfwe197ug\nt/4ONzvnuoh4A/jvnu6z0O8XIuK5wu+gbET8v4gY3MN93kJ+1cHphd9BH0REdQ/3uTwiTmtV9kxE\nXNiDfX49Il5tp/yuiLi5h/o8NiLeavb8oMLP+LJmZTdHxK090Hem8O/SvzUrOywiNkTEEd3dX7M+\nvlJ47w5oVf7ziJjZg/3u2ez9u6nZ4+Ge6K+iwg+wPXAt+a22jyR/w9Y7e6Hfr5JfrjOe/BKaMyPi\na73Q7xXA2cB3gVHAl+n4ZrTd5RrgcOA44G+BCeR/3j3tPGAK8HXg48D/Z+/e4+2s6gP/f75AMAaG\nYD1yK4ZR0BicliGpKK0WhanYsa0ttWWORmwdRx212Dj1OiAXrR28kA6OjGgrGMFM0fLzNlpUjKBT\n8ZIDgppELsEjGGK2YLiEA4R8f3+s58A+O+ecZO+cZ+/kPJ/367VfybP2etZ37cvZz/7utZ71LAc+\nGRHPqznu6cC7KEuzH0x5jeu2HDge+APKNbOeByzuQ1yAVwL3AcdR3lvvioiT+hS7USLiZcBlwHBm\nrhx0f2bYacAmyt/LBcBHgE8D/w84FvgKsCIi5tbch36/l99Pmb75CsrjvBm4MiIOrDnuafT/GDTZ\nsaBfn1NQHvODwG8Dr6s7WEQcQrn+4D8Az6AkJFdQ/5TZN1Gum/gxyjHoUOBnNccchE8DT2z/4l/9\n3bwQuLSmmNcA+0fEsdX2CZTPree31TkB+MZMB87MFvAq4JyIWBwR+wGfBC7IzFUzHa/Npym5wR+N\nF0TEk4AXAR+vMe4ocAjl/XsI5fPxl8DVtUTLzMbegCcB24Cja4yxCvhhR9nfdZbVEHd/4AHgL/v4\nfO4HjAGntJU9AbgfOL/GuPtSvsQ8u6P8Y8ClfXjcbwJu7dNzvD/lgP4nbWUHVI+/tue4irMKuLqj\n7DvAe/v02FfV/RiniHsxcEU/HyPweuAu4Hl9fqy1P8ed7yPKgfZe4JK2soOrz+bj+tGHqqzW9zLl\nengPAqe2le1D+eHkv9X8fPf1GDSoY0HHY15dd5yOmMdSflB9cj/jtj3evn02Us5tPb2j7DrgXTXH\n/Szwsbbt1wA/qznmamBZ9f8rgLdV363mAYdVn1NPrTH+h4C1lATvemBOH17fDwNfbNt+M3BTH99f\njwOuBT5bV4xGjfxExFER8amIuCUiNgO3AgnUOkRMeRHbfRt4WkTU+YvQIkpSUMuQ4RSOBOZQLn4L\nQGbeDayrOe5RlA+ir1ZTLO6NiHspv64eWXPsfnsq5QvT98YLMvMe6n+Ox93Qsb0BOKhPsZvipZQE\n6Pcy85uD7kxNHn0fZeY2yi98N7aVjY9Q1/ne6vd7+UjK3+6jVyDPzK2Uz8tFNcaF/h+DBnUsaPf9\nPsYC+AFwFfDDiLg8Il7dhxG9prkM+NO2KVkvA+oeFf8Gj430PI+SAK0Ffocy6nNHZtY53f0tlM+N\nlwIvy/6cu/Yx4IURcWi1/UrKj4D98nHKDygvrytAo5If4IuUX59eTZnqcBxlSHrfQXaqJg8MIOb4\ngbTfF4/av/r3PwLHtN2OpnxgzCZTPcf9Wo2s84M3ad7nSN2uo0yt6MfU2EGZ7H002UG9zvdWv9/L\n0/3tzrYL7g3qWNDu/n4Gy8xtmflCyvSgHwF/BayNiCP62Y8+2cb2x5w5k1WcYV8A9gZeHBGHU5KR\nuqa8jbsaeF5EHAM8lJk3VWUvoKYpbx2OpIww7QU8peZYAGTm9ZQfh06LiMWU71Izfl7TZCLiDMpU\nxj/MzNr+hhvzpSUifg14OvCezFyVmeuAJ/Yp/HM6to+nDCHWeWC4iTLtoJ/nY9wMbKXt8UbEEyjP\ne51+TJlOckRm3tpxu6Pm2P12C+U5Pm68ICIOAJ42sB5ppt1CObC+JCI+NOjOaMbcTEm4njteEBH7\nAIQAVIYAACAASURBVL8FrKk5dr+PQYM6FgxcZn47M8+hTIN7mHKOV90eoiQF/bKJcm4G8OgxqPYv\n5pk5Rhl5WQoMA2szs3MEd6ZdQ5la/tc8luh8gzIadAJ1nZNCWaWQktz9H+BM4OPV+Tf98A+Uc47+\nEvhaP75LRVmk6gzgzzLztjpjNWmp67spUyteExF3AkdQ5j3345epJ0fEB4CPUk7+fyOwrM6Amflg\nRJwHvC8iHqacSPwk4JmZWctJa5l5f0T8I/D+iLiL8gH5Hso86Npk5n3V87s8IvYGvgXMpwxLb87M\nT9YZv5+qx/oJ4APVKjSbgLMpz/Fs+/W4sTLz5urE3lURsTUza/28UP0yc0tE/G/K5+PdlJPS3wo8\nHvjHmsP39Rg0qGPBIEXEcZQfG78C/IKS+A1Rfpyr223As6tRpvuAu2r+cfXrwCsj4ovAZsqiSltr\njNfuMsoI0DOBFXUHy8xfRcSNlITr9VXx1cA/Ub5Df6PG8O+lJF5/BWyhzG75OGURkbpdRlm05NWU\nUwhqFRHPpIwunQesiYiDq7seqqbMzqjGJD+ZmRFxKmVloRspc49Pp/4hy6T8gT6eMv95K7A8M/+h\n5rhk5rlV4nMOZdh0A2VVpTq9hTJX8/OUk5g/SPnjrVVmnhkRG4G3U86L+RUwQvnwmG2WUV7HLwD3\nAO8DnkwZ6avToJOrQcfvh0cfY2b+pFp9bDwBeks/4/c5xs6W1dmHfng7ZbrQCuDfUM5LeWFmbq45\n7iCOQZMdC+bXHHPcIF7fe4DfpSyAcwDwU+DNmfmVPsT+AHAJJdGaSxmFGa0x3t9VMb5ASX7OBP5t\njfHafZ2yGMzTKKvr9cM3gN+s/iUz746IHwNPysyb6wgYESdQvqM+f3z6V0ScBlwfEa/NzIvqiDsu\nM++NiH+mJFyfqzNW5bcon1FnVLdxV1NWZ55RUe+PA5LqFhHzgDsoB9p+npTYCBHxKWBrZp426L5I\n3YqIVcB1mdmXa67tKX2RNL2I+Bpw42ycedCYc36k2SIi/n1E/KeIeGp1MuKnKL909uPXmcaIiL0j\n4mjK+RE/GnR/JEmqW0QcGBF/Qjmn6cJB96cOjZn2Js0yf0M5efghynUInpuZdw22S7POv6MsS3wV\n9U8XleqyO03v2J36Imly1wEHAm+tVrebdZz2JkmSJKkRnPYmSZIkqRFMfiRJkiQ1gsmPJEmSpEYw\n+ZEkSZLUCCY/kiRJkhrB5EeSJElSI5j8SJJ6EhGrIuL8AcW+OCKuGERsSdKey+RHkjRQEXFERGyL\niN+sMcYJVYwDOsoHlsBJkvrP5EeSNGgB1H3F7fEYUUvjEXPqaFeSNLNMfiRJuywiXh4R34uIeyJi\nQ0RcFhFParv/wKrsFxGxJSLWRcQrq7tvrf69vhqd+XoP8SMi3hERt1btXxcRf1rddwQw3ubdEfFI\nRHw8Ii4GTgDeVMV9JCIWVPv8u4j4UkTcGxF3RsSKiHhiW7xVEfGhiFgeEZuAf+n6SZMk9d0+g+6A\nJGlWmAOcAawDDgLOBy4BXlzd/x7gGcDJwC+Bo4DHV/cdB3wXOBH4MfBQD/HfCbwMeA1wM/C7wCcj\n4hfAt4A/BT4DPA24F3iAMgr0dOBG4Mxqe1NEzAeuAj4KvAmYB5wHXA6c1BbzNOB/A7/dQ38lSQNg\n8iNJ2mWZeUnb5m0R8dfAdyJiXmZuAZ4MXJeZ11V1Rtvqb6r+vSszf9Ft7IjYF3gHcFJmfqetD88D\nXpuZ34yIu8ZjZeY9bfs+BGzJzE1tZW8ERjLzzLayVwOjEXFUZt5cFd+cmW/vtr+SpMEx+ZEk7bKI\nWAKcBRwDPIHHplUvANZSRkj+uar3FeCzmfntGQp/FGV05qsR0X5OzxxgpIf2jgFOjIh7O8oTOJIy\nsgTw/R7aliQNkMmPJGmXRMQ8yjkvX6ZMPdsEHFGV7QuQmf9SnU/zYuA/AFdFxP/KzLfOQBf2r/79\nj8DPO+57sMf2Pg+8le0XSNjQ9v/7e2hbkjRAJj+SpF31DOCJwDsy8w6AiDius1Jm/hJYAayIiG8B\n76MkGOPn+OzdY/wfU5KcIzLzW1PUmSrGQ5OUjQCnAD/NzG099kmStBtytTdJ0q4apSQRp0fEUyLi\njyiLHzwqIs6JiD+KiCMj4pnAH1CSFoBfUBYgeFFEHNR5LZ4dycz7gA8AyyPitIh4akQcGxFvjIhX\nVNV+Spm29ocRMRQR+1XltwH/oVrt7Q+qsg8Dvwb8n4j4raq9k6sV4mpZKluS1B8mP5KkXiVAZraA\nVwIvpZzf8znKKmp7US1fTVlN7R+BHwDfALYCw9X+jwB/BbwWuAP4bNcdKYsTnAu8nZJUfZkyDW59\ndf/PKeck/Q/gTuBD1a4fALZRprd9LiIWZOYG4Heq/l8J3EBZve7uzBy/HlHd1yWSJNUgHvsclyRp\n11TX7vk4Jdm5rePuH2bmDX3v1A5ExAmU6wC9IDOvGXR/JEn18ZwfSVId/iUze1lpTZKk2jjtTZLU\ndxGxNCK+HxFbIuKXEbEyIg5vu//eiNgaEY9ExP3V/7PafmdV54SIuLZqY21EnNQRY0FEXFjdtyUi\nWhFxeUQcsZN9fHZE/EtE/KrqwzciwguaStIezORHklSH+RHxxPbb+B0R8d+BTwDrgGXAcuAk4Oq2\nxQ6OAb5HWQzhbuBjwLuAm4CzI+LPgZXAF4G3AfsBn25byADgWcBzqnp/RbnW0EnAqoiYO13nI+JE\n4GrKstdnUy6iOh/4ekT8Vk/PiCRp4DznR5I0Y6pzfi6e5K7MzL2rUZebgTMy87y2/Y4GrgfelZn/\noypbBfwuMJyZl1dlT6csqvAI8NuZ+b2q/PcoixP8RWauqMoel5kTrvNTLcF9LfCKzLysKtvunJ+I\nWAfcnJkvbtv3cZTFFG7KzBftyvMkSRoMz/mRJM20BF5PGaXpdAplZbVPt48GUUZ4bgJeQFmRbdx9\n44kPQGb+JCJ+Bdw+nvhUvlP9+9S2uo8mPhGxD3AAcCtlJGkxcNlknY+Ifw88DXh3Rx8DuApYOtl+\nkqTdn8mPJKkO35tiwYOjKFOub57kvuSxi5GOu32SepuBn03YMfOe6hI8Txgvq6a2vRP4C+DXKcnL\neJz50/T9adW/K6a4f1tEzM/MzdO0IUnaDZn8SJL6aS/KdXVeVP3b6b6O7UemaGeq8vaLkP4vyvWH\nllOmum2mJD7/xPTnvI7f998o1yWaTGc/JUl7AJMfSVI/3UJJUG7LzMlGf2bSnwKXZOZbxwuq83YO\n3MF+t1T/3puZX6+rc5Kk/nO1N0lSP11BGfE5a7I7I+LXZjDWI2x/nDsd2HsH+62mJEB/07F6HAAR\nMTQz3ZMk9ZsjP5KkmRZT3ZGZt0bEGcB7I+IpwGeBeykLFfwxcBFw/gz144vAKyLiHsoqbcdTlrpu\nTdfnzMyIeDXwJeBHEXExcAflvKEXUKbPvWSG+ihJ6iOTH0nSTJv2GgqZeV61lPQyyrV7oCxg8C/A\n53eirdzJ8tOBrcDLgLnAt4D/QFkSu3P/CduZeXVEHA+cCbwB+DfABsqqchdN8/AkSbsxr/MjSZIk\nqRF6OucnIt4QEesj4oGIuDYinrWT+/2niNgWEVdMct+5EfHziNgSEV+NiKN66ZskSZIkTabr5Cci\nTgU+SDlZ9VjKMqBX7ugE0Oqq3u8HrpnkvrcBbwReCxwH3F+1uW+3/ZMkSZKkyXQ97S0irgW+k5lv\nqraDMlf7gsx83xT77AVcDXwc+F1gfmae0nb/z4H3Z+byavsAYCPwyvYre0uSJElSr7oa+YmIOcAS\n4KrxsizZ09coq+hM5SzgF5l58SRtPgU4pKPNeygnlU7XpiRJkiTttG5XexuiXB9hY0f5RmDhZDtE\nxO8AfwkcM0Wbh1BW2ZmszUO67J8kSZIkTWqmlroOJll2NCL2Bz4J/JfMvHsm2qzafSJwMnAbMNZl\nu5IkSZJmj7nAvwWuzMxfTlex2+SnRbli9sEd5Qex/cgNwJHAEcAXqnODoJpqFxEPUUaL7qQkOgd3\ntHEQcN0U/TgZuKzLvkuSJEmavV4OfGq6Cl0lP5n5cESsplwh+/Pw6IIHJwEXTLLLGuA3Osr+Ftif\ncvG5n2Xm1oi4s2rjhqrNA4BnAx+eoiu3AVx66aUsWrSom4cAwLJly1i+fHnX++0q487OmMad3XGb\n9FiNO7vjNumxGnf2xjTu7I7ba8w1a9awdOlSqHKE6fQy7e184BNVEvRdyhW65wGXAETECuD2zHxn\nZj4E/Lh954j4FWWdhDVtxX8PnBERN1edfjdwO/C5KfowBrBo0SIWL17c9QOYP39+T/vtKuPOzpjG\nnd1xm/RYjTu74zbpsRp39sY07uyOOwMxd3g6TNfJT2ZeXl3T51zKVLXrgZMzc1NV5XBga5dtvi8i\n5gEXAQcC3wR+v0qeJEmSJGmX9bTgQWZeCFw4xX0n7mDfv5yi/Gzg7F76I0mSJEk70tV1fiRJkiRp\nT7X32WefPeg+dO2cc845FHjta1/7Wg499NCe2viN3+hch6E/jDs7Yxp3dsdt0mM17uyO26THatzZ\nG9O4sztuLzE3bNjARz/6UYCPnn322RumqxuZk15KZ7cWEYuB1atXrx7ICWCSJEmSdg8jIyMsWbIE\nYElmjkxX12lvkiRJkhrB5EeSJElSI5j8SJIkSWoEkx9JkiRJjdDTdX5mk9HRUVqt1oSyoaEhFixY\nMKAeSZIkSapDo5Of0dFRFi1cyJaxsQnl8+bOZc26dSZAkiRJ0izS6GlvrVaLLWNjXAqsrm6XAlvG\nxrYbDZIkSZK0Z2v0yM+4RYBXC5IkSZJmt0aP/EiSJElqDpMfSZIkSY1g8iNJkiSpEUx+JEmSJDWC\nyY8kSZKkRjD5kSRJktQIJj+SJEmSGsHkR5IkSVIjmPxIkiRJagSTH0mSJEmNYPIjSZIkqRFMfiRJ\nkiQ1gsmPJEmSpEboKfmJiDdExPqIeCAiro2IZ01T908i4nsRcXdE3BcR10XE0o46F0fEto7bl3rp\nmyRJkiRNZp9ud4iIU4EPAq8BvgssA66MiKdnZmuSXX4JvAdYCzwE/CFwcURszMyvttX7MvAXQFTb\nD3bbN0mSJEmaSi8jP8uAizJzRWauBV4HbAFeNVnlzLwmMz+Xmesyc31mXgDcADy3o+qDmbkpM39R\n3Tb30DdJkiRJmlRXyU9EzAGWAFeNl2VmAl8Djt/JNk4Cng5c3XHX8yNiY0SsjYgLI+LXuumbJEmS\nJE2n22lvQ8DewMaO8o3Awql2iogDgDuAxwFbgddn5tfbqnwZ+GdgPXAk8HfAlyLi+Cq5kiRJkqRd\n0vU5P1MIYLok5V7gGGB/4CRgeUTcmpnXAGTm5W11fxQRNwK3AM8HVs1QHyVJkiQ1WLfJTwt4BDi4\no/wgth8NelQ1enNrtXlDRBwNvAO4Zor66yOiBRzFNMnPsmXLmD9//oSy4eFhhoeHd/AwJEmSJO1p\nVq5cycqVKyeUbd6880sFdJX8ZObDEbGaMnrzeYCIiGr7gi6a2osyBW5SEXE48ERgw3SNLF++nMWL\nF3cRVpIkSdKearKBjpGREZYsWbJT+/cy7e184BNVEjS+1PU84BKAiFgB3J6Z76y23w58nzKN7XHA\ni4GllFXiiIj9gLMo5/zcSRntOQ/4CXBlD/2TJEmSpO10nfxk5uURMQScS5n+dj1wcmZuqqocTlnU\nYNx+wIer8gco1/t5eWZ+prr/EeA3gdOAA4GfU5Ked2Xmw10/IkmSJEmaRE8LHmTmhcCFU9x3Ysf2\nmcCZ07Q1Bryol35IkiRJ0s6aqdXe9gijo6O0Wq1Ht9esWTPA3kiSJEnqp8YkP6Ojoyx8xkLGHhgb\ndFckSZIkDUBjkp9Wq1USn1Mol2oFuAmvIiRJkiQ1RGOSn0cNAYdV/29NV1G7q87piwBDQ0MsWLBg\nQD2SJEnSnqB5yY/2aKOjoyxcuIixsS0TyufOnce6dWtMgCRJkjSlvQbdAakbrVarSnwuBVZXt0sZ\nG9uy3WiQJEmS1M6RH+2hFgGLB90JSZIk7UEc+ZEkSZLUCCY/kiRJkhrB5EeSJElSI5j8SJIkSWoE\nkx9JkiRJjWDyI0mSJKkRTH4kSZIkNYLJjyRJkqRGMPmRJEmS1AgmP5IkSZIaweRHkiRJUiOY/EiS\nJElqBJMfSZIkSY1g8iNJkiSpEUx+JEmSJDWCyY8kSZKkRjD5kSRJktQIJj+SJEmSGqGn5Cci3hAR\n6yPigYi4NiKeNU3dP4mI70XE3RFxX0RcFxFLJ6l3bkT8PCK2RMRXI+KoXvomSZIkSZPpOvmJiFOB\nDwJnAccCPwCujIihKXb5JfAe4DnAbwAXAxdHxO+1tfk24I3Aa4HjgPurNvfttn+SJEmSNJleRn6W\nARdl5orMXAu8DtgCvGqyypl5TWZ+LjPXZeb6zLwAuAF4blu1NwHvzswvZOYPgdOAw4A/7qF/kiRJ\nkrSdrpKfiJgDLAGuGi/LzAS+Bhy/k22cBDwduLrafgpwSEeb9wDf2dk2JUmSJGlH9umy/hCwN7Cx\no3wjsHCqnSLiAOAO4HHAVuD1mfn16u5DgJyizUO67J8kSZIkTarb5GcqQUlgpnIvcAywP3ASsDwi\nbs3Ma3ahTZYtW8b8+fMnlA0PDzM8PLxTnZYkSZK051i5ciUrV66cULZ58+ad3r/b5KcFPAIc3FF+\nENuP3Dyqmhp3a7V5Q0QcDbwDuAa4k5LoHNzRxkHAddN1Zvny5SxevLib/kuSJEnaQ0020DEyMsKS\nJUt2av+uzvnJzIeB1ZTRGwAiIqrtf+2iqb0oU+DIzPWUBKi9zQOAZ3fZpiRJkiRNqZdpb+cDn4iI\n1cB3Kau/zQMuAYiIFcDtmfnOavvtwPeBWygJz4uBpZRV4sb9PXBGRNwM3Aa8G7gd+FwP/ZMkSZKk\n7XSd/GTm5dU1fc6lTFW7Hjg5MzdVVQ6nLGowbj/gw1X5A8Ba4OWZ+Zm2Nt8XEfOAi4ADgW8Cv5+Z\nD3X/kCRJkiRpez0teJCZFwIXTnHfiR3bZwJn7kSbZwNn99IfSZIkSdqRXi5yKkmSJEl7HJMfSZIk\nSY1g8iNJkiSpEUx+JEmSJDWCyY8kSZKkRjD5kSRJktQIJj+SJEmSGsHkR5IkSVIjmPxIkiRJagST\nH0mSJEmNYPIjSZIkqRFMfiRJkiQ1wj6D7kBdRkdHabVaj26vWbNmgL2RJEmSNGizMvkZHR1l4cJF\njI1tGXRXJEmSJO0mZuW0t1arVSU+lwKrq9u7B9spSZIkSQM1K0d+HrMIWFz932lvkiRJUpPNypEf\nSZIkSepk8iNJkiSpEUx+JEmSJDWCyY8kSZKkRjD5kSRJktQIJj+SJEmSGsHkR5IkSVIjmPxIkiRJ\naoSekp+IeENErI+IByLi2oh41jR1Xx0R10TEXdXtq531I+LiiNjWcftSL32TJEmSpMl0nfxExKnA\nB4GzgGOBHwBXRsTQFLucAHwKeD7wHOBnwFci4tCOel8GDgYOqW7D3fZNkiRJkqbSy8jPMuCizFyR\nmWuB1wFbgFdNVjkzX5GZH8nMGzLzJ8Crq7gndVR9MDM3ZeYvqtvmHvomSZIkSZPqKvmJiDnAEuCq\n8bLMTOBrwPE72cx+wBzgro7y50fExohYGxEXRsSvddM3SZIkSZpOtyM/Q8DewMaO8o2UqWo74zzg\nDkrCNO7LwGnAicBbKVPlvhQR0WX/JEmSJGlS+8xQOwHkDitFvB34c+CEzHxovDwzL2+r9qOIuBG4\nhXKe0Kqp2lu2bBnz58+fUDY8PMzChQu76rwkSZKk3d/KlStZuXLlhLLNm3f+bJluk58W8AhlYYJ2\nB7H9aNAEEfE3lFGdkzLzR9PVzcz1EdECjmKa5Gf58uUsXrx4u/KRkZHpmpckSZK0BxoeHmZ4eOK6\naCMjIyxZsmSn9u9q2ltmPgyspm2xgmpq2knAv061X0S8BfjvwMmZed2O4kTE4cATgQ3d9E+SJEmS\nptLLam/nA6+JiNMi4hnAR4B5wCUAEbEiIt47Xjki3gq8m7Ia3GhEHFzd9qvu3y8i3hcRz46IIyLi\nJOCzwE+AK3flwUmSJEnSuK7P+cnMy6tr+pxLmf52PWVEZ1NV5XBga9su/5WyuttnOpo6p2rjEeA3\nKQseHAj8nJL0vKsaaZIkSZKkXdbTggeZeSFw4RT3ndix/ZQdtDUGvKiXfkiSJEnSzupl2pskSZIk\n7XFMfiRJkiQ1gsmPJEmSpEYw+ZEkSZLUCCY/kiRJkhrB5EeSJElSI5j8SJIkSWoEkx9JkiRJjWDy\nI0mSJKkRTH4kSZIkNYLJjyRJkqRGMPmRJEmS1AgmP5IkSZIaweRHkiRJUiOY/EiSJElqBJMfSZIk\nSY1g8iNJkiSpEUx+JEmSJDXCPoPugDRT1qxZM2F7aGiIBQsWDKg3kiRJ2t2Y/GgW2AABS5cunVA6\n9/FzWbd2nQmQJEmSAJMfzQq/ggROAYaqohaMXTFGq9Uy+ZEkSRJg8qPZZAg4bNCdkCRJ0u7KBQ8k\nSZIkNYLJjyRJkqRG6Cn5iYg3RMT6iHggIq6NiGdNU/fVEXFNRNxV3b46Wf2IODcifh4RW6o6R/XS\nN0mSJEmaTNfJT0ScCnwQOAs4FvgBcGVEDE2xywnAp4DnA88BfgZ8JSIObWvzbcAbgdcCxwH3V23u\n223/JEmSJGkyvYz8LAMuyswVmbkWeB2wBXjVZJUz8xWZ+ZHMvCEzfwK8uop7Ulu1NwHvzswvZOYP\ngdMop67/cQ/9kyRJkqTtdJX8RMQcYAlw1XhZZibwNeD4nWxmP2AOcFfV5lOAQzravAf4ThdtSpIk\nSdK0uh35GQL2BjZ2lG+kJDA74zzgDkrCRLVf7mKbkiRJkjStmbrOT1ASmOkrRbwd+HPghMx8aFfb\nXLZsGfPnz59QNjw8zMKFC3fUFUmSJEl7mJUrV7Jy5coJZZs3b97p/btNflrAI8DBHeUHsf3IzQQR\n8TfAW4GTMvNHbXfdSUl0Du5o4yDguunaXL58OYsXL96ufGRkZLrdJEmSJO2BhoeHGR4enlA2MjLC\nkiVLdmr/rqa9ZebDwGraFiuIiKi2/3Wq/SLiLcB/B07OzAkJTWaupyRA7W0eADx7ujYlSZIkqRu9\nTHs7H/hERKwGvktZ/W0ecAlARKwAbs/Md1bbbwXOBYaB0YgYHzW6LzPvr/7/98AZEXEzcBvwbuB2\n4HM99E+SJEmSttN18pOZl1fX9DmXMlXtesqIzqaqyuHA1rZd/itldbfPdDR1TtUGmfm+iJgHXAQc\nCHwT+P2dOC9IkiRJknZKTwseZOaFwIVT3Hdix/ZTdrLNs4Gze+mPJEmSJO1ILxc5lSRJkqQ9jsmP\nJEmSpEYw+ZEkSZLUCCY/kiRJkhrB5EeSJElSI5j8SJIkSWoEkx9JkiRJjWDyI0mSJKkRTH4kSZIk\nNcI+g+6AVKc1a9ZM2B4aGmLBggUD6o0kSZIGyeRHs9N9ZVhz6dKlE4rnzZ3LmnXrTIAkSZIayGlv\nmp3GYBtwKbC6ul0KbBkbo9VqDbRrkiRJGgxHfjSrLQIWD7oTkiRJ2i048iNJkiSpEUx+JEmSJDWC\nyY8kSZKkRjD5kSRJktQIJj+SJEmSGsHkR5IkSVIjmPxIkiRJagSTH0mSJEmNYPIjSZIkqRFMfiRJ\nkiQ1gsmPJEmSpEboKfmJiDdExPqIeCAiro2IZ01T9+iI+ExVf1tEnD5JnbOq+9pvP+6lb5IkSZI0\nma6Tn4g4FfggcBZwLPAD4MqIGJpil3nALcDbgA3TNP1D4GDgkOr23G77JkmSJElT6WXkZxlwUWau\nyMy1wOuALcCrJqucmd/PzLdl5uXAQ9O0uzUzN2XmL6rbXT30TZIkSZImtU83lSNiDrAEeO94WWZm\nRHwNOH4X+/K0iLgDGAO+DbwjM3+2i21KkiRJ2gmjo6O0Wq0JZUNDQyxYsGBAPZp5XSU/wBCwN7Cx\no3wjsHAX+nEt8BfAOuBQ4Gzgmoj4d5l5/y60K0mSJGkHRkdHWfiMhYw9MDahfO7j57Ju7bpZkwB1\nm/xMJYDsdefMvLJt84cR8V3gp8CfAxfvYt8kSZIkTaPVapXE5xTKcAdAC8auGKPVajU2+WkBj1AW\nJmh3ENuPBvUsMzdHxE+Ao6art2zZMubPnz+hbHh4mIULd2UQSpIkSWqoIeCwQXdiaitXrmTlypUT\nyjZv3rzT+3eV/GTmwxGxGjgJ+DxARES1fUE3bU0nIvYHjgRWTFdv+fLlLF68eLvykZGRmeqKJEmS\npN3E8PAww8PDE8pGRkZYsmTJTu3fy7S384FPVEnQdymrv80DLgGIiBXA7Zn5zmp7DnA0ZWrcvsCv\nR8QxwH2ZeUtV5/3AFyhT3X4dOAfYCkxM6yRJkiSpR10nP5l5eXVNn3Mp09+uB07OzE1VlcMpicu4\nw4DreOycoL+pblcDJ7bt8yngicAm4FvAczLzl932T5IkSZIm09OCB5l5IXDhFPed2LH9U3ZwPaHM\nHJ7ufkmSJEnaVb1c5FSSJEmS9jgztdS1JEl7rCZc2E+SZPIjSWq40dFRFi1cyJaxiRf2mzd3LmvW\nzZ4L+0mSnPYmSWq4VqvFlrExLgVWV7dLgS1jY9uNBkmS9myO/EiSBCwCtr9ynCRpNnHkR5IkSVIj\nmPxIkiRJagSnvUmSGqVzZbc1a9YMsDeSpH4y+ZEkNcbo6CgLn7GQsQfGdlxZkjTrmPxIkhqj1WqV\nxOcUYKgqvAlYNcBOSZL6xuRHktQ8Q8Bh1f9dzVqSGsMFDyRJkiQ1gsmPJEmSpEYw+ZEkSZLUCCY/\nkiRJkhrB5EeSJElSI5j8SJIkSWoEl7qWJEmSNKU1a9ZM2B4aGmLBggUD6s2uMfmRJEmStL37yjSx\npUuXTiieN3cua9at2yMTIKe9SZIkSdreGGwDLgVWV7dLgS1jY7Rae+YVoh35kSRJkjSlRcDibefb\nKgAAGndJREFUQXdihpj8SJIkSQ0zOjo6YfSm87ye2crkR5IkSWqQ0dFRFi5cxNjYlkF3pe8850eS\nJElqkFarVSU+7WfzvHuwneqTnpKfiHhDRKyPiAci4tqIeNY0dY+OiM9U9bdFxOm72qYkSZKkXTV+\nNs9i4CkD7kt/dJ38RMSpwAeBs4BjgR8AV0bE0BS7zANuAd4GbJihNiVJkiSpK72M/CwDLsrMFZm5\nFngdsAV41WSVM/P7mfm2zLwceGgm2pQkSZKkbnWV/ETEHGAJcNV4WWYm8DXg+F46UEebkiRJktSp\n25GfIWBvYGNH+UbgkB77UEebkiRJkjTBTK32FkDOUFt1tilJkiSpobq9zk8LeAQ4uKP8ILYfuam9\nzWXLljF//vwJZcPDwyxcuLDHrkiSJEnaXa1cuZKVK1dOKNu8efNO799V8pOZD0fEauAk4PMAERHV\n9gXdtDUTbS5fvpzFixdvVz4yMtJLVyRJkiTtxoaHhxkeHp5QNjIywpIlS3Zq/25HfgDOBz5RJSzf\npazUNg+4BCAiVgC3Z+Y7q+05wNGUaWz7Ar8eEccA92XmLTvTpiRJkiTtqq6Tn8y8vLr+zrmUqWrX\nAydn5qaqyuHA1rZdDgOu47Hzd/6mul0NnLiTbUqSJEnSLull5IfMvBC4cIr7TuzY/ik7sbDCdG1K\nkiRJ0q6aqdXeJEmSJGm3ZvIjSZIkqRFMfiRJkiQ1gsmPJEmSpEYw+ZEkSZLUCCY/kiRJkhrB5EeS\nJElSI5j8SJIkSWoEkx9JkiRJjbDPoDsgSVJdRkdHabVaj26vWbNmgL2RJA2ayY8kaVYaHR1l4cJF\njI1tGXRXJEm7CZMfST3r/FUdYGhoiAULFgyoR9JjWq1WlfhcCiyqSr8EnDm4TkmSBsrkR1JPRkdH\nWbRwIVvGxiaUz5s7lzXr1pkAaTeyCFhc/d9pb5LUZC54IKknrVaLLWNjXAqsrm6XAlvGxrYbDZIk\nSdodOPIjaZe0/6YuSZK0O3PkR5IkSVIjmPxIkiRJagSTH0mSJEmNYPIjSZIkqRFMfiRJkiQ1gsmP\nJEmSpEYw+ZEkSZLUCCY/kiRJkhrB5EeSJElSI5j8SJIkSWqEnpKfiHhDRKyPiAci4tqIeNYO6v9Z\nRKyp6v8gIn6/4/6LI2Jbx+1LvfRNkiRJkibTdfITEacCHwTOAo4FfgBcGRFDU9Q/HvgU8DHg3wOf\nBT4bEUd3VP0ycDBwSHUb7rZvkiRJkjSVXkZ+lgEXZeaKzFwLvA7YArxqivpvAr6cmedn5rrMPAsY\nAd7YUe/BzNyUmb+obpt76JskSZIkTWqfbipHxBxgCfDe8bLMzIj4GnD8FLsdTxkpancl8JKOsudH\nxEbgbuDrwBmZeVc3/ZM0M0ZHR2m1WhPKhoaGWLBgwYB6JEmStOu6Sn6AIWBvYGNH+UZg4RT7HDJF\n/UPatr8M/DOwHjgS+DvgSxFxfGZml32UtAtGR0dZuHARY2NbJpTPnTuPdevWmABJkqQ9VrfJz1QC\n6CZJmVA/My9vu+9HEXEjcAvwfGDVVI0sW7aM+fPnTygbHh5m4cKp8jBJO9JqtarE51JgUVW6hrGx\npbRaLZMfSZI0MCtXrmTlypUTyjZv3vmzZbpNflrAI5SFCdodxPajO+Pu7LI+mbk+IlrAUUyT/Cxf\nvpzFixdvVz4yMjLVLpJ22iJg+78vSZKkQRkeHmZ4eOK6aCMjIyxZsmSn9u9qwYPMfBhYDZw0XhYR\nUW3/6xS7fbu9fuX3qvJJRcThwBOBDd30T5IkSZKm0su0t/OBT0TEauC7lNXf5gGXAETECuD2zHxn\nVf9/AldHxJuB/0tZwnoJ8F+q+vtRls3+Z8oo0VHAecBPKAsjSJIkSdIu6zr5yczLq2v6nEuZznY9\ncHJmbqqqHA5sbav/7YgYBv62ut0EvCQzf1xVeQT4TeA04EDg55Sk513VSJMkaQa5mp8kqal6WvAg\nMy8ELpzivhMnKftnysjOZPXHgBf10g9JUndczU+S1GQztdqbJNXCUYqZ5Wp+kqQmM/mRtNsaHR1l\n4TMWMvbA2ITyuY+fy7q16/yivktczU/qhT/ISHs2kx9Ju61Wq1USn1Mol1gGaMHYFWOOUkjqO6eN\nSns+kx9JO23NmjWT/r92Q8Bh/QsnSZNx2qi05zP5kbQTNkDA0qVLB90R1agzoXUqjzQVp41KeyqT\nH0k74VeQTJx+dhOwanA90kyaPLn13CpJ0mxj8iNp57VPP2tNV7F+jlLMpEmSW8+tkiTNQiY/kvYs\n98FebD9KMW/uXNasc5Ril3hulSRplttr0B2QpK6MwTbK6carq9ulwJaxse2Wn5UkSWrnyI+kPZKn\nG0tqEq8vJM0Mkx9J0pQ8t0oaPK8vJM0ckx9J0vY8t0rabXh9IWnmmPxIkrbXdm7VY1+1YOmYK8BJ\ng+OEX2lXmfxIkqbkVy1J0mziam+SJEmSGsHkR5IkSVIjOO1NPXPZTUnS7s5jlaR2Jj/qictuSpJ2\nd6OjoyxauJAtY2MTyl21UGoukx/1xGU3JUm7u1arxZaxsVm9aqHX4pK6Y/KjXeRaUJKk/utmOls/\njlSdSciDDz7I4x73uAllM5uYbIDY/lpccx8/l3VrHdWSpmLyI0mS9ii719TryZOQvSjXymo3s9Pt\nfgUJnAIMVUUtGLti9oxqSXUw+ZEkSXuU3Wvq9SRJyE2wbVWfLhI8BBw2c81Js53JjyRpIFyFS7tu\nN5p63Z6EVG/r3ah3kirNvM7PjYMJu3LlSuPWzde2Pwb0PA8irq9tPUZHR1n4jIUsWbJkwm3hMxYy\nOjran05Aoz4zmvZenu1/Q9PFXbNmDSMjI4/e6vqbatpr27S4s/WY21PyExFviIj1EfFARFwbEc/a\nQf0/i4g1Vf0fRMTvT1Ln3Ij4eURsiYivRsRRvfRtpzToYNe4uL62/bEbHNz7xde2Hq1Wi7EHxspU\nodcAC4BTYOyBse1Gg2rVoM+MpryXx7/4f+QjH9luEYK+GOTn433li93SpUsn/KiwaGE9Pyo05T3V\n1Liz9Zjb9bS3iDgV+CDlcPVdYBlwZUQ8PTO3O2JFxPHAp4C3Af8XeBnw2Yg4NjN/XNV5G/BG4JXA\neuA9VZuLMvOhnh6ZJGn3Nz5VaC6PnS8h9WT7hQeuueaaAfZnAMbKIguzeWlvaVf1MvKzDLgoM1dk\n5lrgdcAW4FVT1H8T8OXMPD8z12XmWcAIJdlpr/PuzPxCZv4QOI1yOPzjHvonSZIap23hgfHRxBcM\ntkeDMn6u0WIeS4IkFV2N/ETEHGAJ8N7xsszMiPgacPwUux1PGSlqdyXwkqrNpwKHAFe1tXlPRHyn\n2vfybvqowRufZrB582ZGRkb6cK0DzRadJ8APZMqKBm42XLRxssUc2j8L/XysUfto4hMG3BdJ2xn0\nYjfdTnsbAvYGNnaUbwQWTrHPIVPUP6T6/8GU32qmq9NpLkz9xeix8i9RBnwB/l/55ybgHuAGYHT7\nWuu3a6M7mzZt2u4F3Wuvvdi2bRu33347l1122YSycUNDQzzpSU+a8ZjAo3E7Y+5K3Mmf4+uAiVMO\nlixZQlBe4HZz992Xz1xxBYceeugMxN29X1uo7/WtI+4On+MW5Xme4ed4w4YNnHLKS3noobHt76wx\nLjTntYXB/Q11Ptb169c/FnP8tb0Rgkku2ljX58Ug3sttZvrzEZrzXh7Ua9u0uNCc99RUcev+PjVZ\nzH7E3d0+H+fMeRzvf/95Pb+2bX2Zu6M+RGbnx+40lSMOBe4Ajs/M77SVvw94bmb+9iT7PAiclpn/\n1Fb2euCMzDysOifoW8Bhmbmxrc7lwNbMfNkkbb4MuGynOy5JkiRptnt5Zn5qugrdjvy0gEcoozXt\nDmL7kZtxd+6g/p2UH/sO7mjjIMaHErZ3JfBy4DZg+p/WJEmSJM1mc4F/S8kRptVV8pOZD0fEauAk\n4PMAERHV9gVT7PbtSe7/vaqczFwfEXdWdW6o2jwAeDbw4Sn68UvKCnKSJEmS9K87U6nrpa6B84FP\nVEnQ+FLX84BLACJiBXB7Zr6zqv8/gasj4s2Upa6HKYsm/Je2Nv8eOCMibqaM5rwbuB34XA/9kyRJ\nkqTtdJ38ZOblETEEnEuZqnY9cHJmbqqqHA5sbav/7YgYBv62ut0EvGT8Gj9VnfdFxDzgIuBA4JvA\n73uNH0mSJEkzpasFDyRJkiRpT9XLRU7VhYhYFRHnD7ofg9SE5yAiPhoRv4yIRyLiNwfdnzoM+nUc\nVPyIuDgiruhTrEY+x5Ik9Usv5/xIahMRLwJOA06gLH/fmn4P9ehPgIcHEPd0yoqUkrTbiYhVwHWZ\n+eZB90XaE5j8SLvuKGBD+7WvNPMy81cDinvvIOJKmhkRMSczB/HDiaTdUKOmvUXEyRHxzYi4OyJa\nEfGFiHhqH0LvExEfiohfRcSmiDi3DzGJ4q0RcVNEjEXEbRHxjppjzouIFRFxb0TcUa3yV7vqsb4j\nIm6NiC0RcV1E/Gkf4l5MWcZ9QURsi4hb+xBz/4i4LCLuq57jv+7jdKW9IuK8aorfhog4qw8xgWZM\ne5sk9osjYnO1aMysUL2OF0TE8oi4KyLujIj/XH12fDwi7qk+s15Ucx/+Z7/fyxGxb/XYN0bEA9Xx\n6LdqjrmqOv709Rg02bGgX3/DbY95eURsAv6l7phV3JdGxA3VMagVEV+JiMfXHPNiyqyDN1XHoEci\nYkHNMddHxOkdZddFxLtqjPmaiLh9kvLPR8THaor5BxFxd9v2MdVz/LdtZR+LiE/UEHuo+lx6e1vZ\n8RHxYES8YKbjtcV4RfXendNR/rmIuKTGuEe0vX+3td2+Xke8RiU/wH7ABylLbZ9IuWDr/9eHuH9B\nma7zLMoUmjdHxH/uQ9z/AbwVOAdYBLyMqS9GO1M+ADwP+EPghcDzKc933d4JLAVeAxwNLAc+GRHP\nqznu6cC7KEuzH0x5jeu2HDge+APKNbOeByzuQ1yAVwL3AcdR3lvvioiT+hS7USLiZcBlwHBmrhx0\nf2bYacAmyt/LBcBHgE8D/w84FvgKsCIi5tbch36/l99Pmb75CsrjvBm4MiIOrDnuafT/GDTZsaBf\nn1NQHvODwG8Dr6s7WEQcQrn+4D8Az6AkJFdQ/5TZN1Gum/gxyjHoUOBnNccchE8DT2z/4l/93bwQ\nuLSmmNcA+0fEsdX2CZTPree31TkB+MZMB87MFvAq4JyIWBwR+wGfBC7IzFUzHa/Npym5wR+NF0TE\nk4AXAR+vMe4ocAjl/XsI5fPxl8DVtUTLzMbegCcB24Cja4yxCvhhR9nfdZbVEHd/4AHgL/v4fO4H\njAGntJU9AbgfOL/GuPtSvsQ8u6P8Y8ClfXjcbwJu7dNzvD/lgP4nbWUHVI+/tue4irMKuLqj7DvA\ne/v02FfV/RiniHsxcEU/HyPweuAu4Hl9fqy1P8ed7yPKgfZe4JK2soOrz+bj+tGHqqzW9zLlengP\nAqe2le1D+eHkv9X8fPf1GDSoY0HHY15dd5yOmMdSflB9cj/jtj3evn02Us5tPb2j7DrgXTXH/Szw\nsbbt1wA/qznmamBZ9f8rgLdV363mAYdVn1NPrTH+h4C1lATvemBOH17fDwNfbNt+M3BTH99fjwOu\nBT5bV4xGjfxExFER8amIuCUiNgO3AgnUOkRMeRHbfRt4WkTU+YvQIkpSUMuQ4RSOBOZQLn4LQGbe\nDayrOe5RlA+ir1ZTLO6NiHspv64eWXPsfnsq5QvT98YLMvMe6n+Ox93Qsb0BOKhPsZvipZQE6Pcy\n85uD7kxNHn0fZeY2yi98N7aVjY9Q1/ne6vd7+UjK3+6jVyDPzK2Uz8tFNcaF/h+DBnUsaPf9PsYC\n+AFwFfDDiLg8Il7dhxG9prkM+NO2KVkvA+oeFf8Gj430PI+SAK0Ffocy6nNHZtY53f0tlM+NlwIv\ny/6cu/Yx4IURcWi1/UrKj4D98nHKDygvrytAo5If4IuUX59eTZnqcBxlSHrfQXaqJg8MIOb4gbTf\nF4/av/r3PwLHtN2OpnxgzCZTPcf9Wo2s84M3ad7nSN2uo0yt6MfU2EGZ7H002UG9zvdWv9/L0/3t\nzrYL7g3qWNDu/n4Gy8xtmflCyvSgHwF/BayNiCP62Y8+2cb2x5w5k1WcYV8A9gZeHBGHU5KRuqa8\njbsaeF5EHAM8lJk3VWUvoKYpbx2OpIww7QU8peZYAGTm9ZQfh06LiMWU71Izfl7TZCLiDMpUxj/M\nzNr+hhvzpSUifg14OvCezFyVmeuAJ/Yp/HM6to+nDCHWeWC4iTLtoJ/nY9wMbKXt8UbEEyjPe51+\nTJlOckRm3tpxu6Pm2P12C+U5Pm68ICIOAJ42sB5ppt1CObC+JCI+NOjOaMbcTEm4njteEBH7AL8F\nrKk5dr+PQYM6FgxcZn47M8+hTIN7mHKOV90eoiQF/bKJcm4G8OgxqPYv5pk5Rhl5WQoMA2szs3ME\nd6ZdQ5la/tc8luh8gzIadAJ1nZNCWaWQktz9H+BM4OPV+Tf98A+Uc47+EvhaP75LRVmk6gzgzzLz\ntjpjNWmp67spUyteExF3AkdQ5j3345epJ0fEB4CPUk7+fyOwrM6AmflgRJwHvC8iHqacSPwk4JmZ\nWctJa5l5f0T8I/D+iLiL8gH5Hso86Npk5n3V87s8IvYGvgXMpwxLb87MT9YZv5+qx/oJ4APVKjSb\ngLMpz/Fs+/W4sTLz5urE3lURsTUza/28UP0yc0tE/G/K5+PdlJPS3wo8HvjHmsP39Rg0qGPBIEXE\ncZQfG78C/IKS+A1Rfpyr223As6tRpvuAu2r+cfXrwCsj4ovAZsqiSltrjNfuMsoI0DOBFXUHy8xf\nRcSNlITr9VXx1cA/Ub5Df6PG8O+lJF5/BWyhzG75OGURkbpdRlm05NWUUwhqFRHPpIwunQesiYiD\nq7seqqbMzqjGJD+ZmRFxKmVloRspc49Pp/4hy6T8gT6eMv95K7A8M/+h5rhk5rlV4nMOZdh0A2VV\npTq9hTJX8/OUk5g/SPnjrVVmnhkRG4G3U86L+RUwQvnwmG2WUV7HLwD3AO8DnkwZ6avToJOrQcfv\nh0cfY2b+pFp9bDwBeks/4/c5xs6W1dmHfng7ZbrQCuDfUM5LeWFmbq457iCOQZMdC+bXHHPcIF7f\ne4DfpSyAcwDwU+DNmfmVPsT+AHAJJdGaSxmFGf3/27u7UMvKOo7j3x82QpPUlOldM6VjSIlTJAZl\nTWhgZQllF73QeBPNjWVQDI44hBK9IXphL9RFykQSkWEFaS/jGE2EFXMscUgYTAfGkXNyBhwb8eD4\n72I9JzfHlzj7zNr7zFnfDxzW2c+z1vN/OBd7n/9ez/NfPcb7eovxK7rkZwfwxh7jjbqHrhjMOXTV\n9SbhXuD8dqSqjiTZB5xRVfv7CJhkM93/qO9bWP6VZAtwf5KtVfX9PuIuqKqjSe6gS7h+0Wes5gK6\n96jr2s+CP9BVZz6h0u+XA5L6lmQtcJDug3aSmxIHIcntwLNVtWXac5GWKsluYKaqJvLMtZNlLpJe\nXpLfAw+sxpUHg9nzI60WSd6W5BNJzmqbEW+n+6ZzEt/ODEaSU5K8hW5/xIPTno8kSX1Lsi7JR+n2\nNH132vPpw2CWvUmrzJfpNg/P0z2H4KKqOjzdKa0659GVJd5F/8tFpb6spOUdK2kukl7cDLAO2Naq\n2606LnuTJEmSNAgue5MkSZI0CCY/kiRJkgbB5EeSJEnSIJj8SJIkSRoEkx9JkiRJg2DyI0mSJGkQ\nTH4kSZIkDYLJjyRpLEl2J7lpSrFvTfLzacSWJJ28TH4kSVOVZEOS55Kc32OMzS3Gqxe1Ty2BkyRN\nnsmPJGnaAtSEYqSXwZM1fYwrSTqxTH4kScuW5NNJ/prkySSHkvw4yRkj/eta22ySY0keSnJl6364\nHe9vd2fuGSN+kmxP8nAbfybJFa1vA7Aw5pEkx5P8MMmtwGbg6hb3eJL17Zrzkvw6ydEkjyfZmeT0\nkXi7k9yS5OYkc8DdS/6jSZIm7hXTnoAkaVVYA1wHPAScCdwE3AZc1vq/CpwLXAo8AWwEXtn6LgT+\nAlwM7APmx4h/LfAp4HPAfuC9wI+SzAJ7gCuAnwHnAEeBp+nuAr0ZeADY0V7PJXkNsAv4AXA1sBb4\nJvBT4JKRmFuA7wHvGmO+kqQpMPmRJC1bVd028vKRJF8E7kuytqqOAW8AZqpqpp1zYOT8uXY8XFWz\nS42d5FRgO3BJVd03Mof3AFur6o9JDi/EqqonR66dB45V1dxI21XA3qraMdL2WeBAko1Vtb8176+q\na5Y6X0nS9Jj8SJKWLck7gK8Am4DX8vyy6vXAP+nukNzRzvstcGdV/fkEhd9Id3fmd0lG9/SsAfaO\nMd4m4OIkRxe1F3A23Z0lgL+NMbYkaYpMfiRJy5JkLd2el7volp7NARta26kAVXV3209zGfB+YFeS\nb1fVthMwhdPa8UPAY4v6nhlzvF8C23hhgYRDI7//Z4yxJUlTZPIjSVquc4HTge1VdRAgyYWLT6qq\nJ4CdwM4ke4Bv0SUYC3t8Thkz/j66JGdDVe15iXNeKsb8i7TtBT4GPFpVz405J0nSCmS1N0nSch2g\nSyK+kORNSS6nK37wP0muT3J5krOTvBX4MF3SAjBLV4DgA0nOXPwsnv+nqp4CbgRuTrIlyVlJ3p7k\nqiSfaac9Srds7SNJXp/kVa39EeCd7VlDC9XcvgO8DvhJkgvaeJe2CnG9lMqWJE2GyY8kaVwFUFX/\nBq4EPg48SHc350uLzp0Hvgb8HbgXeBb4ZLv+OPB5YCtwELhzyRPpihPcAFxDl1TdRbcM7l+t/zG6\nPUnfAB4HbmmX3ggcb9fMJllfVYeAd9N9Rv4G+Add9bojVbXwPKK+n0skSepBnn8flyRJkqTVyzs/\nkiRJkgbBggeSpBWnlZkuXlhtrYAPVtWfJj8rSdLJzuRHkrQSbXqZvoMTm4UkaVVxz48kSZKkQXDP\njyRJkqRBMPmRJEmSNAgmP5IkSZIGweRHkiRJ0iCY/EiSJEkaBJMfSZIkSYNg8iNJkiRpEP4LLPiK\n/syQhCEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x18182e750>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "letter_prop = table/table.sum().astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>last_letter</th>\n",
       "      <th>d</th>\n",
       "      <th>n</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1880</th>\n",
       "      <td>0.083055</td>\n",
       "      <td>0.153213</td>\n",
       "      <td>0.075760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1881</th>\n",
       "      <td>0.083247</td>\n",
       "      <td>0.153214</td>\n",
       "      <td>0.077451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1882</th>\n",
       "      <td>0.085340</td>\n",
       "      <td>0.149560</td>\n",
       "      <td>0.077537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1883</th>\n",
       "      <td>0.084066</td>\n",
       "      <td>0.151646</td>\n",
       "      <td>0.079144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1884</th>\n",
       "      <td>0.086120</td>\n",
       "      <td>0.149915</td>\n",
       "      <td>0.080405</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "last_letter         d         n         y\n",
       "year                                     \n",
       "1880         0.083055  0.153213  0.075760\n",
       "1881         0.083247  0.153214  0.077451\n",
       "1882         0.085340  0.149560  0.077537\n",
       "1883         0.084066  0.151646  0.079144\n",
       "1884         0.086120  0.149915  0.080405"
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dny_ts = letter_prop.ix[['d','n','y'],'M'].T\n",
    "dny_ts.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x18563b310>"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dny_ts.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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8QgghMo7WmuFbh/P131+jH2hg9nTx5Lsm39G5aueHdmC0aiuhEaHEWeOwaitx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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1850e2f50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([False, False, False, False, False, False, False, False, False, False], dtype=bool)"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_names = top1000.name.unique()\n",
    "mask = np.array(['lesl' in x.lower() for x in all_names] )\n",
    "mask[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Leslie', 'Lesley', 'Leslee', 'Lesli'], dtype=object)"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lesley_like = all_names[mask]\n",
    "lesley_like[:4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "filtered = top1000[top1000.name.isin(lesley_like)]\n",
    "table = filtered.pivot_table(values = 'births',index = 'year',columns ='sex',aggfunc = np.sum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "table = table.div(table.sum(1),axis = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>sex</th>\n",
       "      <th>F</th>\n",
       "      <th>M</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "sex     F   M\n",
       "year         \n",
       "2006  1.0 NaN\n",
       "2007  1.0 NaN\n",
       "2008  1.0 NaN\n",
       "2009  1.0 NaN\n",
       "2010  1.0 NaN"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "table.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x185640250>"
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "table.plot(style=['M','k-','F','k--'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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wqGCtSyGqwQBA5ERCQ0PZAmBnxmwjTn18CiEzQqD0nH1BrQcDAJETCQ0NZQuA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\njGmHLAAwxhhj2qH/D2WclIH1NVrcAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x17ecd9290>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "a= range(1,5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3, 4]"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "a= [1,2,3,45,6]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 157,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'b' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-158-bcdf01ac482b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0ma\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mb\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m: name 'b' is not defined"
     ]
    }
   ],
   "source": [
    "a = [1,'a','b']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
